Whale optimization and sine-cosine optimization algorithms with cellular topology for parameter identification of chaotic systems and Schottky barrier diode models

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dc.authoridTUZUN OZMEN, Ozge/0000-0002-5204-3737
dc.authoridTurgut, Mert Sinan/0000-0002-5739-2119
dc.authoridTurgut, Oguz Emrah/0000-0003-3556-8889
dc.contributor.authorTurgut, Mert Sinan
dc.contributor.authorSagban, H. Muzaffer
dc.contributor.authorTurgut, Oguz Emrah
dc.contributor.authorOzmen, Ozge Tuzun
dc.date.accessioned2021-12-01T18:49:44Z
dc.date.available2021-12-01T18:49:44Z
dc.date.issued2021
dc.department[Belirlenecek]en_US
dc.description.abstractThis research study aims to enhance the optimization accuracy of the two recently emerged metaheuristics of whale and sine-cosine optimizers by means of the balanced improvements in intensification and diversification phases of the algorithms provided by cellular automata (CA). Stagnation at the early phases of the iterations, which leads to entrapment in local optimum points in the search space, is one of the inherent drawbacks of the metaheuristic algorithms. As a favorable solution alternative to this problem, different types of cellular topologies are implemented into these two algorithms with a view to ameliorating their search mechanisms. Exploitation of the fertile areas in the search domain is maintained by the interaction between the topological neighbors, whereas the improved exploration is resulted from the smooth diffusion of the available population information among the structured neighbors. Numerical experiments have been carried out to assess the optimization performance of the proposed cellular-based algorithms. Optimization benchmark problems comprised of unimodal and multimodal test functions have been applied and numerical results have been compared with those found by some of the state-of-the-art literature optimizers including particle swarm optimization, differential evolution, artificial cooperative search and differential search. Cellular variants have been outperformed by the base algorithms for multimodal benchmark problems of Levy and Penalized1 functions. Then, the proposed cellular algorithms have been applied to two different parameter identification cases in order to test their efficiencies on real-world optimization problems. Extensive performance evaluations on different parameter optimization cases reveal that incorporating the CA concepts on these algorithms not only improves the optimization accuracy but also provides considerable robustness to acquired solutions.en_US
dc.identifier.doi10.1007/s00500-020-05227-6
dc.identifier.endpage1409en_US
dc.identifier.issn1432-7643
dc.identifier.issn1433-7479
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85089014518en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1365en_US
dc.identifier.urihttps://doi.org/10.1007/s00500-020-05227-6
dc.identifier.urihttps://hdl.handle.net/20.500.12684/10771
dc.identifier.volume25en_US
dc.identifier.wosWOS:000555358400004en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofSoft Computingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCellular automataen_US
dc.subjectChaotic systemsen_US
dc.subjectParameter identificationen_US
dc.subjectSchottky barrier diodesen_US
dc.subjectSine-cosine algorithmen_US
dc.subjectWhale optimizationen_US
dc.subjectParticle Swarm Optimizationen_US
dc.subjectGrey Wolf Optimizeren_US
dc.subjectDifferential Evolutionen_US
dc.subjectSearch Algorithmen_US
dc.subjectGlobal Optimizationen_US
dc.subjectHarmony Searchen_US
dc.subjectExtractionen_US
dc.subjectDesignen_US
dc.subjectBehavioren_US
dc.titleWhale optimization and sine-cosine optimization algorithms with cellular topology for parameter identification of chaotic systems and Schottky barrier diode modelsen_US
dc.typeArticleen_US

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